基于图像引导滤波的人脸光照预处理算法

针对人脸识别中人脸图像光照预处理的问题,提出一种基于图像引导滤波的人脸光照预处理算法。根据自定义光照标准函数对引导图像和输入图像进行分类,经指数或对数非线性变换调整后进行直方图均衡化处理。采用图像引导滤波对图像细节进行增强,使变换后的图像更清晰。利用空域高通滤波来抑制局部锐化现象。在YaleB人脸数据库上进行验证,结果表明,该算法在识别性能上明显优于经典的主成分分析法,识别率可以提高2%~8%。

Illumination Preprocessing Algorithm of Face Based on Image Guided Filtering

Aiming at the problem of illumination preprocessing of face recognition. A new preprocessing algorithm for human face illumination is presented based on image guided filtering. Guided images and input images are classified by an illumination standard function, and Histogram Equalization（HE） is used to adjust images after they are processed by one of non-linear transformation algorithms, logarithm or exponential. Image guided filtering is applied to enhance image details in order to make the processed images clearer. A spatial domain high pass filter is adopted to restrain local sharpening phenomenon. A series of experiments are performed on the YaleB human face image database. Experimental results show that the proposed method is obviously superior to principal component analysis. The recognition rate can be improved by 2%-8% in comparison with other methods.